Triple
T983132
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ruins of the medieval coronation basilica |
E21214
|
entity |
| Predicate | hasNameInLocalLanguage |
P21937
|
FINISHED |
| Object | Középkori koronázó bazilika romjai |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Középkori koronázó bazilika romjai | Statement: [Ruins of the medieval coronation basilica, hasNameInLocalLanguage, Középkori koronázó bazilika romjai]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNameInLocalLanguage Context triple: [Ruins of the medieval coronation basilica, hasNameInLocalLanguage, Középkori koronázó bazilika romjai]
-
A.
hasEnglishName
Indicates that an entity is associated with a name expressed in the English language.
-
B.
hasOfficialNameInEnglish
Indicates that an entity has an officially recognized name expressed in the English language.
-
C.
hasNameInPolish
Indicates that an entity is associated with a specific name or label expressed in the Polish language.
-
D.
hasNameInSpanish
Indicates that an entity is associated with a specific name expressed in the Spanish language.
-
E.
hasLatinName
Indicates that an entity is associated with a specific Latin (scientific) name.
- F. None of above. chosen
Provenance (4 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69a493c383dc8190a03257f22d4b4183 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b49284ac8190b1d7c828d728893c |
completed | March 1, 2026, 9:50 p.m. |
| PD | Predicate disambiguation | batch_69a4b2aa219081908a6b0ef786b4aa52 |
completed | March 1, 2026, 9:42 p.m. |
| PDg | Predicate description generation | batch_69a4b345f890819092b51bf8128da461 |
completed | March 1, 2026, 9:44 p.m. |
Created at: March 1, 2026, 7:41 p.m.